Monte Carlo Simulations Versus Historical Simulations (Updated To 2018)
A second classical approach to studying retirement withdrawal rates is to use Monte Carlo simulations that are parameterized to the same historical data used in historical simulations. This can be done either by randomly drawing past returns from the historical data to construct thirty-year sequences of returns (a process known as “bootstrapping”), or by simulating returns from a statistical distribution (usually a multivariate normal or lognormal distribution) that matches the historical parameters for asset returns, standard deviations, and correlations.
Pfau, Wade D. PhD, "Monte Carlo Simulations Versus Historical Simulations (Updated To 2018)" (2018). Faculty Publications. 886.